An ACO-Based Tool-Path Optimizer for 3-D Printing Applications

Kai-Yin Fok, Chi-Tsun Cheng, Nuwan Ganganath, Herbert Ho-Ching Iu, Chi K. Tse
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="" style="color: black;">IEEE Transactions on Industrial Informatics</a> </i> &nbsp;
Layered additive manufacturing, also known as 3D printing, has revolutionized transitional manufacturing processes. Fabrication of 3D models with complex structures is now feasible with 3D printing technologies. By performing careful tool-path optimization, the printing process can be speeded up, while the visual quality of printed objects can be improved simultaneously. The optimization process can be perceived as an undirected rural postman problem (URPP) with multiple constraints. In this
more &raquo; ... er, a tool-path optimizer is proposed, which further optimizes solutions generated from a slicer software to alleviate visual artifacts in 3D printing and shortens print time. The proposed optimizer is based on a modified ant colony optimization (ACO), which exploits unique properties in 3D printing. Experiment results verify that the proposed optimizer can deliver significant improvements in computational time, print time, and visual quality of printed objects over optimizers based on conventional URPP and ACO solvers.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/tii.2018.2889740</a> <a target="_blank" rel="external noopener" href="">fatcat:g2fj7yk5undmjg4yjfwqbzjeee</a> </span>
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