Journal
POLYMER ENGINEERING AND SCIENCE
Volume -, Issue -, Pages -Publisher
WILEY
DOI: 10.1002/pen.26556
Keywords
3D printing; composites; impact resistance; mechanical properties; thermoplastics
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Polylactic acid (PLA) is widely used in fused filament fabrication (FFF). However, its narrow processing window and low mechanical properties limit its usefulness. PLA composites have been developed to enhance its properties. This study examines the effect of nozzle temperature, printing speed, and nominal porosity on the impact strength of PLA/iron composites using FFF. Response surface methodology is used to optimize the experimental design. The results show that the nominal porosity has the most significant effect on impact resistance, while the nozzle temperature has the least effect. The lowest nozzle temperature, lowest nominal porosity, and a printing speed of 50 mm/s are found to be the optimal conditions.
Polylactic acid (PLA) is the most widely used material in the fused filament fabrication (FFF) technique, which is a biocompatible thermoplastic. However, PLA's usefulness is limited by its narrow processing window and relatively low mechanical properties. Therefore, PLA composites have been developed to enhance its properties for FFF printing. A key challenge in producing composite parts via this method is to find the correlation between the mechanical properties of the parts and the process parameters. This knowledge is essential for optimizing the printing process to achieve the desired mechanical properties for composite parts industries such as aerospace, automotive, and medical, where high-performance composite materials are crucial. The ability to control and predict the mechanical properties of FFF-printed composite parts is critical for their successful integration into these industries. In this study, the effect of nozzle temperature (NT), printing speed (PS), and nominal porosity (POR) on the impact strength and specific impact strength of PLA/iron composites was examined using FFF. Response surface methodology (RSM) was used to optimize the experimental design. The results revealed that POR had the most significant effect on the impact resistance data, while NT had the least effect. Reducing the POR led to improved impact resistance in the samples. Multi-objective optimization results showed that the lowest NT (190degree celsius), the lowest POR (30%), and a PS of 50 mm/s were the optimal conditions for multiple objectives. RSM was also utilized to develop mathematical models of impact properties, focusing on varying NT, POR, and PS, which can be used to predict desired impact properties.
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