Causal technological model for predicting void fraction and energy consumption in material extrusion process of polylactic acid

The rapid expansion of Additive Manufacturing (AM) technologies within the framework of Industry 4.0 raises important questions about their sustainability. Specifically, the widespread use of Material Extrusion (MEx) processes for polymeric materials necessitates a thorough evaluation of the possible balance between performance efficiency and sustainability, highlighting the need for further research into optimizing process parameters to ensure high product quality and reduced energy consumption. The present work focuses on Fused Filament Fabrication (FFF) technology, investigating the relationship between sustainability and print quality. A causal technology model is proposed to elucidate this relationship, underlining the impact of process parameters on defect generation and energy use. A real-time monitoring system for energy consumption measurements was employed to create an energy model that accounts for each component of the CreatBot F430 printer. An image analysis procedure was performed on a special configuration of the HIROX RH-2000 digital microscope to determine the void fraction of each sample. An experimental campaign was conducted, producing single-layer samples in polylactic acid (PLA) following a full factorial plan with four process parameters. A void fraction of up to 18 % was observed, with energy consumption per sample ranging between 638 J and 8843 J. Statistical analysis was performed to assess the impact of each process parameter and to determine operational ranges through the Response Surfaces Method. These results showed good agreement with the predicted conditions, demonstrating the model's effectiveness in supporting decision-making processes in technology selection.

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Publication Details

Journal
Journal of Manufacturing Processes
Published
2024-09-02
DOI
https://doi.org/10.1016/j.jmapro.2024.08.061
Citations
5
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
1.02
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article

Causal technological model for predicting void fraction and energy consumption in material extrusion process of polylactic acid

Marco Mazzarisi, Michele Dassisti, Fulvio Lavecchia, Fabrizia Devito
5 citations
Journal of Manufacturing Processes
Additive Manufacturing and 3D Printing Technologies
1.02
article

Causal technological model for predicting void fraction and energy consumption in material extrusion process of polylactic acid

Marco Mazzarisi, Michele Dassisti, Fulvio Lavecchia, Fabrizia Devito
article en
5 citations

Abstract

The rapid expansion of Additive Manufacturing (AM) technologies within the framework of Industry 4.0 raises important questions about their sustainability. Specifically, the widespread use of Material Extrusion (MEx) processes for polymeric materials necessitates a thorough evaluation of the possible balance between performance efficiency and sustainability, highlighting the need for further research into optimizing process parameters to ensure high product quality and reduced energy consumption. The present work focuses on Fused Filament Fabrication (FFF) technology, investigating the relationship between sustainability and print quality. A causal technology model is proposed to elucidate this relationship, underlining the impact of process parameters on defect generation and energy use. A real-time monitoring system for energy consumption measurements was employed to create an energy model that accounts for each component of the CreatBot F430 printer. An image analysis procedure was performed on a special configuration of the HIROX RH-2000 digital microscope to determine the void fraction of each sample. An experimental campaign was conducted, producing single-layer samples in polylactic acid (PLA) following a full factorial plan with four process parameters. A void fraction of up to 18 % was observed, with energy consumption per sample ranging between 638 J and 8843 J. Statistical analysis was performed to assess the impact of each process parameter and to determine operational ranges through the Response Surfaces Method. These results showed good agreement with the predicted conditions, demonstrating the model's effectiveness in supporting decision-making processes in technology selection.

Journal of Manufacturing ProcessesVol. 129
Istituto Universitario di Studi Superiori di Pavia (IT)
Affordable and clean energy
Openalex Percentile: Top 25%
Additive Manufacturing and 3D Printing Technologies
1.02
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