TY - JOUR
T1 - Mathematical Modelling of Fused Deposition Modeling (FDM) 3D Printing of Poly Vinyl Alcohol Parts through Statistical Design of Experiments Approach
AU - Moradi, Mahmoud
AU - Karamimoghadam, Mojtaba
AU - Meiabadi, Mohammad Saleh
AU - Casalino, Giuseppe
AU - Ghaleeh, Mohammad
AU - Baby, Bobymon
AU - Ganapathi, Harikrishna
AU - Jose , Jomal
AU - Abdulla , Muhammed Shahzad
AU - Tallon , Paul
AU - Shamsborhan, Mahmoud
AU - Rezayat, Mohammad
AU - Paul , Satyam
AU - Khodadad , Davood
PY - 2023/7/7
Y1 - 2023/7/7
N2 - This paper explores the 3D printing of poly vinyl alcohol (PVA) using the fused deposition mod-eling (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.
AB - This paper explores the 3D printing of poly vinyl alcohol (PVA) using the fused deposition mod-eling (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.
KW - additive manufacturing
KW - fused deposition modeling
KW - 3D printing
KW - infill percentage
KW - optimization
U2 - 10.3390/math11133022
DO - 10.3390/math11133022
M3 - Article
SN - 2227-7390
VL - 11
JO - Mathematics
JF - Mathematics
IS - 13
M1 - 3022
ER -