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An evolutional algorithm for automatic 2D layer segmentation in laser-aided additive manufacturing
Additive Manufacturing ( IF 11.0 ) Pub Date : 2021-09-21 , DOI: 10.1016/j.addma.2021.102342
N. Liu 1 , K. Ren 2 , W. Zhang 3 , Y.F. Zhang 3 , Y.X. Chew 2 , G.J. Bi 2 , J.Y.H. Fuh 3
Affiliation  

Path planning is an important task in laser aided additive manufacturing (LAAM). The sliced 2D layers usually need to be partitioned into sub-regions such that appropriate filling toolpaths can be designed for different sub-regions. However, reported approaches for 2D layer segmentation generally require manual interaction that is tedious and time-consuming. To increase segmentation efficiency, this paper proposes an autonomous approach based on evolutional computation for 2D layer segmentation. The algorithm works in an identify-and-segment manner. Specifically, the largest quasi-quadrilateral is identified and segmented from the target layer iteration by iteration. Results from case studies have validated the effectiveness and efficacy of the developed algorithm. To further improve its performance, a roughing-finishing strategy is proposed. Via multi-processing, the strategy can remarkably increase the solution variety without significant sacrifice of solution quality and search time, thus providing great application potential in LAAM path planning. The developed segmentation algorithm has also been experimentally validated by comparing with the benchmarking toolpath generated by Powermill. With the developed segmentation algorithm, the quality of the deposited samples could be significantly improved. To the best of the authors’ knowledge, this work is the first to address automatic 2D layer segmentation problem in LAAM process. Therefore, it can be a valuable supplement to the state of the art in this area.



中文翻译:

激光辅助增材制造中自动二维层分割的进化算法

路径规划是激光辅助增材制造 (LAAM) 中的一项重要任务。切片的二维图层通常需要划分为子区域,以便可以为不同的子区域设计适当的填充刀具路径。然而,已报告的 2D 层分割方法通常需要繁琐且耗时的手动交互。为了提高分割效率,本文提出了一种基于进化计算的 2D 层分割的自主方法。该算法以识别和分割的方式工作。具体来说,从目标层迭代中通过迭代识别和分割最大的准四边形。案例研究的结果验证了所开发算法的有效性和功效。为了进一步提高其性能,提出了粗加工-精加工策略。通过多处理,该策略可以在不显着牺牲解质量和搜索时间的情况下显着增加解的多样性,从而在LAAM路径规划中具有巨大的应用潜力。通过与 Powermill 生成的基准刀具路径进行比较,开发的分割算法也得到了实验验证。使用开发的分割算法,可以显着提高沉积样品的质量。据作者所知,这项工作是第一个解决 LAAM 过程中自动 2D 层分割问题的工作。因此,它可以成为该领域现有技术的宝贵补充。从而在LAAM路径规划中提供了巨大的应用潜力。通过与 Powermill 生成的基准刀具路径进行比较,开发的分割算法也得到了实验验证。使用开发的分割算法,可以显着提高沉积样品的质量。据作者所知,这项工作是第一个解决 LAAM 过程中自动 2D 层分割问题的工作。因此,它可以成为该领域现有技术的宝贵补充。从而在LAAM路径规划中提供了巨大的应用潜力。通过与 Powermill 生成的基准刀具路径进行比较,开发的分割算法也得到了实验验证。使用开发的分割算法,可以显着提高沉积样品的质量。据作者所知,这项工作是第一个解决 LAAM 过程中自动 2D 层分割问题的工作。因此,它可以成为该领域现有技术的宝贵补充。这项工作是第一个解决 LAAM 过程中自动 2D 层分割问题的工作。因此,它可以成为该领域现有技术的宝贵补充。这项工作是第一个解决 LAAM 过程中自动 2D 层分割问题的工作。因此,它可以成为该领域现有技术的宝贵补充。

更新日期:2021-09-24
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