Multi-objective optimization of material extrusion parameters to balance mechanical and economic performance

Additive manufacturing, particularly Material Extrusion (MEX), has become increasingly important for producing polymer components in applications where mechanical performance, surface quality, and cost efficiency are simultaneously critical. Polylactic acid (PLA) material is widely used in functional, biomedical, and consumer products; however, inconsistent and sometimes contradictory findings in the literature regarding the effects of MEX process parameters on strength, surface roughness, and cost-related metrics limit reliable process optimization. This study addresses the question of how key MEX parameters can be systematically optimized to balance mechanical performance and economic efficiency while accounting for complex parameter interactions and part anisotropy. A structured design-of-experiments framework was employed, beginning with a fractional factorial screening design to identify the most influential parameters, followed by a central composite design (CCD) integrated with response surface methodology (RSM). Ultimate tensile strength (UTS) and surface roughness were selected as performance indicators, while material consumption and printing time were considered as cost-related objectives. Build orientation and raster angle were parameterized using a continuous-variable approach, moving beyond the conventional use of discrete orientations. Statistical analysis was performed using analysis of variance (ANOVA), and multi-objective optimization (MOO) was applied to determine optimal parameter sets for different application scenarios. The results demonstrate that build orientation, layer thickness, infill percentage, and raster orientation significantly influence both UTS and surface roughness, with pronounced nonlinear effects and interactions, while their relative contributions differ in magnitude and importance. The proposed continuous orientation framework reveals critical transition regions in mechanical behavior that are not captured by traditional discrete orientation studies. The multi-objective optimization model effectively identifies trends of printing parameter combinations that balance conflicting practical printing requirements. This work provides a comprehensive and systematic optimization framework for MEX of PLA, offering deeper insights into orientation-dependent anisotropy and parameter interactions. The findings contribute to more reliable decision-making for cost-effective and sustainable production of high-performance polymer components using MEX.