@ARTICLE{Dostatni_Ewa_Environmental_2023,
 author={Dostatni, Ewa and Dudkowiak, Anna and Rojek, Izabela and Mikołajewski, Dariusz},
 volume={71},
 number={1},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e144478},
 howpublished={online},
 year={2023},
 abstract={This paper attempts to conduct a comparative life cycle environmental analysis of alternative versions of a product that was manufactured with the use of additive technologies. The aim of the paper was to compare the environmental assessment of an additive-manufactured product using two approaches: a traditional one, based on the use of SimaPro software, and the authors’ own concept of a newly developed artificial intelligence (AI) based approach. The structure of the product was identical and the research experiments consisted in changing the materials used in additive manufacturing (from polylactic acid (PLA) to acrylonitrile butadiene styrene (ABS)). The effects of these changes on the environmental factors were observed and a direct comparison of the effects in the different factors was made. SimaPro software with implemented databases was used for the analysis. Missing information on the environmental impact of additive manufacturing of PLA and ABS parts was taken from the literature for the purpose of the study. The novelty of the work lies in the results of a developing concurrent approach based on AI. The results showed that the artificial intelligence approach can be an effective way to analyze life cycle assessment (LCA) even in such complex cases as a 3D printed medical exoskeleton. This approach, which is becoming increasingly useful as the complexity of manufactured products increases, will be developed in future studies.},
 type={Article},
 title={Environmental analysis of a product manufactured with the use of an additive technology – AI-based vs. traditional approaches},
 URL={http://journals.pan.pl/Content/126129/PDF-MASTER/BPASTS_2023_71_1_2967.pdf},
 doi={10.24425/bpasts.2023.144478},
 keywords={additive manufacturing, eco-design, life cycle assessment (LCA), artificial intelligence, neural networks model},
}