Silicone 3D printing: Experimental validation of a reduced-order numerical model for optimal layer deposition
PRICCI Alessio, PERCOCO Gianluca
Abstract. Silicone 3D printing holds a significant potential in soft robotics, stretchable electronics, and custom medical devices. However, challenges such as inconsistent material deposition continue to limit printing precision. This study presents a reduced-order numerical model integrating material rheology, process parameters and nozzle geometry to optimize silicone extrusion. A support vector regression algorithm fine-tunes printing parameters to generate an inlet pressure profile that minimizes over- and under-extrusion and ensures precise layer contouring. Full three-dimensional simulations of non-Newtonian silicone deposition coupled with experimental validation confirm the model’s accuracy in 3D printing a 90-degree rounded corner shape. The proposed approach yields more stable printing paths and reduces layer width variability to 4.21%, compared to 15.02% obtained with constant inlet pressure. Finally, the proposed model is applied to fabricate wavy and multi-strand paths, demonstrating enhanced accuracy and consistency.
Keywords
Material Extrusion, Virtual Modeling, Silicone 3D Printing
Published online 9/10/2025, 10 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: PRICCI Alessio, PERCOCO Gianluca, Silicone 3D printing: Experimental validation of a reduced-order numerical model for optimal layer deposition, Materials Research Proceedings, Vol. 57, pp 180-189, 2025
DOI: https://doi.org/10.21741/9781644903735-21
The article was published as article 21 of the book Italian Manufacturing Association Conference
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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