TY - GEN
T1 - Comparison of real-time geometric analyses to predict warping deformation in fused filament fabrication
AU - Budinoff, Hannah D.
AU - Sun, Yilin
AU - McMains, Sara
N1 - Funding Information:
We thank the reviewers for their constructive feedback. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1752814. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
Copyright © 2020 ASME.
PY - 2020
Y1 - 2020
N2 - This work describes an experimental study to assess if analytical and empirical models can estimate the risk of warping deviation for parts made using fused filament fabrication based on part geometry. We also examine how the accuracy of the prediction varies for different machines and materials. If the predictive models can estimate risk of warping for a given part geometry, they can help enable better design for additive manufacturing so that designers can change part geometry early in the design process to have more easily-manufacturable parts, or choose an alternative orientation to optimize dimensional accuracy at the process planning stage. Specifically, we evaluate the extent to which two analytical models and one empirical model can assess the risk of warping for approximately rectangular parts with varying dimensions. We analyze dimensional accuracy data for parts with different length, height, and fillet type that were printed in ABS and PLA on different fused filament fabrication machines. After evaluating the three models, we found that the empirical model had the best performance over all datapoints. However, the analytical models showed promise but need further refinement on how the prediction of warping deviation depends on part height. Areas for additional research are highlighted.
AB - This work describes an experimental study to assess if analytical and empirical models can estimate the risk of warping deviation for parts made using fused filament fabrication based on part geometry. We also examine how the accuracy of the prediction varies for different machines and materials. If the predictive models can estimate risk of warping for a given part geometry, they can help enable better design for additive manufacturing so that designers can change part geometry early in the design process to have more easily-manufacturable parts, or choose an alternative orientation to optimize dimensional accuracy at the process planning stage. Specifically, we evaluate the extent to which two analytical models and one empirical model can assess the risk of warping for approximately rectangular parts with varying dimensions. We analyze dimensional accuracy data for parts with different length, height, and fillet type that were printed in ABS and PLA on different fused filament fabrication machines. After evaluating the three models, we found that the empirical model had the best performance over all datapoints. However, the analytical models showed promise but need further refinement on how the prediction of warping deviation depends on part height. Areas for additional research are highlighted.
KW - Design for additive manufacturing
KW - Dimensional accuracy
KW - Fused filament fabrication
KW - Warping distortion
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U2 - 10.1115/MSEC2020-8526
DO - 10.1115/MSEC2020-8526
M3 - Conference contribution
AN - SCOPUS:85100919361
T3 - ASME 2020 15th International Manufacturing Science and Engineering Conference, MSEC 2020
BT - Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation
PB - American Society of Mechanical Engineers
T2 - ASME 2020 15th International Manufacturing Science and Engineering Conference, MSEC 2020
Y2 - 3 September 2020
ER -