The significance of sustainability has steadily increased over the last decade, driving industries to explore innovative approaches that mitigate envi-ronmental impact while maintaining operational efficiency. Additive Manufac-turing (AM) has emerged as a promising solution, offering design flexibility and potential for resource efficiency and localized production. However, accu-rately assessing the environmental impact within AM process workflows re-mains challenging, particularly within a life cycle assessment (LCA) context. This paper aims to address this gap by introducing a method to estimate energy consumption in Material Extrusion (MEX) AM and integrate it in the main workflow of the process. The study analyzes two different 3D printers and quantifies the energy contributions of different machine components across var-ious operational conditions. Additionally, it describes regression models with high performance in predicting energy consumption based on key printing pa-rameters such as printing time, nozzle temperature, and building plate tempera-ture. This research contributes to advancing our understanding of energy effi-ciency in AM processes and supports the integration of sustainability considera-tions into additive manufacturing workflows. The findings have implications for optimizing energy usage, minimizing environmental impact, and enhancing the overall sustainability of AM operations.
Enhancing Sustainability Assessment in Material Extrusion Additive Manufacturing
Beatrice Aruanno
Primo
;Alessandro Paoli;Sandro Barone
2025-01-01
Abstract
The significance of sustainability has steadily increased over the last decade, driving industries to explore innovative approaches that mitigate envi-ronmental impact while maintaining operational efficiency. Additive Manufac-turing (AM) has emerged as a promising solution, offering design flexibility and potential for resource efficiency and localized production. However, accu-rately assessing the environmental impact within AM process workflows re-mains challenging, particularly within a life cycle assessment (LCA) context. This paper aims to address this gap by introducing a method to estimate energy consumption in Material Extrusion (MEX) AM and integrate it in the main workflow of the process. The study analyzes two different 3D printers and quantifies the energy contributions of different machine components across var-ious operational conditions. Additionally, it describes regression models with high performance in predicting energy consumption based on key printing pa-rameters such as printing time, nozzle temperature, and building plate tempera-ture. This research contributes to advancing our understanding of energy effi-ciency in AM processes and supports the integration of sustainability considera-tions into additive manufacturing workflows. The findings have implications for optimizing energy usage, minimizing environmental impact, and enhancing the overall sustainability of AM operations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.