Mathematical Modelling of Fused Deposition Modeling (FDM) 3D Printing of Poly Vinyl Alcohol Parts through Statistical Design of Experiments Approach

Author:

Moradi Mahmoud1ORCID,Karamimoghadam Mojtaba2ORCID,Meiabadi Saleh3ORCID,Casalino Giuseppe2ORCID,Ghaleeh Mohammad1,Baby Bobymon1,Ganapathi Harikrishna1,Jose Jomal1,Abdulla Muhammed Shahzad1,Tallon Paul1,Shamsborhan Mahmoud4ORCID,Rezayat Mohammad5ORCID,Paul Satyam6ORCID,Khodadad Davood7ORCID

Affiliation:

1. Faculty of Arts, Science and Technology, University of Northampton, Northampton NN1 5PH, UK

2. Department of Mechanics, Mathematics and Management, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy

3. Department of Mechanical Engineering, École de Technologie Supérieure, 1100 Notre-Dame West, Montreal, QC H3C 1K3, Canada

4. Department of Mechanical Engineering, University of Zakho, Dahouk 42001, Iraq

5. Center for Structural Integrity, Micromechanics, and Reliability of Materials (CIEFMA)-Department of Materials Science and Engineering, Universitat Politècnica de Catalunya-BarcelonaTECH, 08019 Barcelona, Spain

6. Gas Turbine and Transmissions Research Centre, University of Nottingham, Northampton NN1 5PH, UK

7. Department of Applied Physics and Electronics, Umeå Universitet, 90187 Umeå, Sweden

Abstract

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.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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