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Mathematical modelling of fused deposition modeling (FDM) 3D printing of poly vinyl alcohol parts through statistical design of experiments approach
Faculty of Arts, Science and Technology, University of Northampton, Northampton, United Kingdom.
Department of Mechanics, Mathematics and Management, Polytechnic University of Bari, Via Orabona 4, Bari, Italy.
Department of Mechanical Engineering, École de Technologie Supérieure, 1100 Notre-Dame West, QC, Montreal, Canada.
Department of Mechanics, Mathematics and Management, Polytechnic University of Bari, Via Orabona 4, Bari, Italy.
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2023 (English)In: Mathematics, E-ISSN 2227-7390, Vol. 11, no 13, article id 3022Article in journal (Refereed) Published
Abstract [en]

This paper explores the 3D printing of poly vinyl alcohol (PVA) using the fused deposition modeling (FDM) process by conducting statistical modeling and optimization. This study focuses on varying the infill percentage (10–50%) and patterns (Cubic, Gyroid, tri-hexagon and triangle, Grid) as input parameters for the response surface methodology (DOE) while measuring modulus, elongation at break, and weight as experimental responses. To determine the optimal parameters, a regression equation analysis was conducted to identify the most significant parameters. The results indicate that both input parameters significantly impact the output responses. The Design Expert software was utilized to create surface and residual plots, and the interaction between the two input parameters shows that increasing the infill percentage (IP) leads to printing heavier samples, while the patterns do not affect the weight of the parts due to close printing structures. On the contrary, the discrepancy between the predicted and actual responses for the optimal samples is below 15%. This level of error is deemed acceptable for the DOE experiments.

Place, publisher, year, edition, pages
MDPI, 2023. Vol. 11, no 13, article id 3022
Keywords [en]
3D printing, additive manufacturing, fused deposition modeling, infill percentage, optimization
National Category
Manufacturing, Surface and Joining Technology
Identifiers
URN: urn:nbn:se:umu:diva-212308DOI: 10.3390/math11133022ISI: 001028570600001Scopus ID: 2-s2.0-85164962701OAI: oai:DiVA.org:umu-212308DiVA, id: diva2:1784037
Available from: 2023-07-25 Created: 2023-07-25 Last updated: 2025-04-24Bibliographically approved

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Khodadad, Davood

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