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- W3136330185 abstract "Additive manufacturing (AM) has been widely used in many different areas due to its unique advantages, such as the possibility of creating complex shapes, no specific tools required, relatively fast, and less material waste with light-weight designs. The design freedom enabled by AM also allows a component to be highly optimized on its topology and shape according to its function. Currently, there are advanced algorithms that enable designers to perform topology optimization (TO) in the computer-aided design (CAD) phase. However, the optimization results are not considered during the downstream AM process planning like toolpath generation, and the optimized structure may lose its designed performance. Instead of only considering TO in the CAD phase, this work presents a breakthrough in adopting the TO principles in the toolpath planning process and considering the toolpath characteristics presented in the AM processes. Since toolpaths are lines, this paper applies a line-based TO method that uses the principal stress line (PSL) as guidances to the generation of toolpaths to improve structural rigidity. The PSL-based method is efficient, controllable, and able to consider the characteristics of the AM process. The computation results can be directly converted into toolpaths that can be faithfully fabricated and achieve the component function specified in the design phase. Structural tests were performed on the developed method. The experimented results demonstrate that the strategy of applying the PSL-based toolpath planning is a promising direction to incorporate topology optimization from the CAD phase to computer-aided manufacturing (CAM). To the best of our knowledge, this study is the first to explore the use of PSL in the AM's toolpath planning." @default.
- W3136330185 created "2021-03-29" @default.
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- W3136330185 date "2021-04-01" @default.
- W3136330185 modified "2023-10-12" @default.
- W3136330185 title "Function-aware slicing using principal stress line for toolpath planning in additive manufacturing" @default.
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- W3136330185 doi "https://doi.org/10.1016/j.jmapro.2021.02.050" @default.
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