TY - GEN
T1 - Metal-based addictive manufacturing
T2 - 11th IEEE International Conference on Automation Science and Engineering, CASE 2015
AU - Ye, Qian
AU - Chen, Shikui
AU - Chang, Qing
N1 - Publisher Copyright: © 2015 IEEE.
PY - 2015/10/7
Y1 - 2015/10/7
N2 - Though addictive manufacturing (AM) technologies have been widely deployed in academia and industry today, the process has not been thoroughly understood. Modern computation technology enables people to simulate AM processes at high fidelity, which has proven to be an effective way to predict, analyze, and design the AM processes. General methods for AM process simulation include the Finite Element Methods (FEM), Lattice Boltzmann Method (LBM) and Molecular Dynamics (MD). The three methods simulate the underlying physics at different scales and have their strength and limitations. This paper mainly discusses the applications of these simulation and modeling methods to metal-based AM. A basic overview of the fundamental methods for metal-based AM simulation will be provided, followed by a comparison of the pros and cons of those methods in order to provide choice references for different application scenarios.
AB - Though addictive manufacturing (AM) technologies have been widely deployed in academia and industry today, the process has not been thoroughly understood. Modern computation technology enables people to simulate AM processes at high fidelity, which has proven to be an effective way to predict, analyze, and design the AM processes. General methods for AM process simulation include the Finite Element Methods (FEM), Lattice Boltzmann Method (LBM) and Molecular Dynamics (MD). The three methods simulate the underlying physics at different scales and have their strength and limitations. This paper mainly discusses the applications of these simulation and modeling methods to metal-based AM. A basic overview of the fundamental methods for metal-based AM simulation will be provided, followed by a comparison of the pros and cons of those methods in order to provide choice references for different application scenarios.
UR - https://www.scopus.com/pages/publications/84952782634
U2 - 10.1109/CoASE.2015.7294065
DO - 10.1109/CoASE.2015.7294065
M3 - Conference contribution
T3 - IEEE International Conference on Automation Science and Engineering
SP - 218
EP - 224
BT - 2015 IEEE Conference on Automation Science and Engineering
PB - IEEE Computer Society
Y2 - 24 August 2015 through 28 August 2015
ER -