ArticlePolymers2026
Selection of 3D-Printing Optimal Parameters via MCDM for Maximizing the Thermomechanical Response of TPU and PEEK.
Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The optimization of Fused Filament Fabrication (FFF) process parameters is commonly performed using room-temperature mechanical properties as the main decision criteria, while the temperature-dependent thermomechanical response of printed polymers is often not explicitly considered. This limitation is relevant for functional components intended to operate above room temperature, where stiffness retention and viscoelastic behavior may strongly affect service performance. This work proposes an experimental-statistical framework for selecting FFF parameters by integrating Design of Experiments (DoE), tensile testing, dynamic mechanical analysis (DMA), Analysis of Variance (ANOVA), the Entropy Weight Method (EWM) and the VIKOR method. Two materials with contrasting thermomechanical behavior were investigated: a high-performance semicrystalline polymer, Z-PEEK, and an elastomeric thermoplastic, TPU 95A. For each material, a DoE was defined to evaluate the influence of key printing parameters, and the manufactured specimens were characterized in terms of maximum tensile force, maximum deformation and storage modulus at selected temperatures. The ANOVA results showed a material-dependent influence of the processing parameters, with thermally driven parameters being especially relevant for Z-PEEK and deposition-related parameters having a stronger influence on TPU 95A. The EWM-VIKOR analysis identified the optimal Z-PEEK configuration as 400 °C extrusion temperature, 200 °C build plate temperature and 150 °C chamber temperature, whereas the optimal TPU 95A configuration corresponded to 225 °C extrusion temperature, 0.10 mm layer height, 50 mm/s printing speed and 80 °C build plate temperature. Overall, the results demonstrate that incorporating DMA-derived thermomechanical indicators into MCDM-based optimization provides a more application-oriented basis for FFF parameter selection than approaches based only on room-temperature mechanical properties.
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