Jiang Jingchao, Ma Yongsheng
Department of Mechanical Engineering, University of Auckland, Auckland 1142, New Zealand.
Digital Manufacturing and Design Center, Singapore University of Technology and Design, Singapore 486842, Singapore.
Micromachines (Basel). 2020 Jun 28;11(7):633. doi: 10.3390/mi11070633.
Additive manufacturing (AM) is the process of joining materials layer by layer to fabricate products based on 3D models. Due to the layer-by-layer nature of AM, parts with complex geometries, integrated assemblies, customized geometry or multifunctional designs can now be manufactured more easily than traditional subtractive manufacturing. Path planning in AM is an important step in the process of manufacturing products. The final fabricated qualities, properties, etc., will be different when using different path strategies, even using the same AM machine and process parameters. Currently, increasing research studies have been published on path planning strategies with different aims. Due to the rapid development of path planning in AM and various newly proposed strategies, there is a lack of comprehensive reviews on this topic. Therefore, this paper gives a comprehensive understanding of the current status and challenges of AM path planning. This paper reviews and discusses path planning strategies in three categories: improving printed qualities, saving materials/time and achieving objective printed properties. The main findings of this review include: new path planning strategies can be developed by combining some of the strategies in literature with better performance; a path planning platform can be developed to help select the most suitable path planning strategy with required properties; research on path planning considering energy consumption can be carried out in the future; a benchmark model for testing the performance of path planning strategies can be designed; the trade-off among different fabricated properties can be considered as a factor in future path planning design processes; and lastly, machine learning can be a powerful tool to further improve path planning strategies in the future.
增材制造（AM）是基于三维模型将材料逐层连接以制造产品的过程。由于增材制造的逐层特性，具有复杂几何形状、集成组件、定制几何形状或多功能设计的零件现在比传统的减材制造更容易制造。增材制造中的路径规划是产品制造过程中的重要一步。即使使用相同的增材制造机器和工艺参数，采用不同的路径策略时，最终制造的质量、性能等也会有所不同。目前，针对不同目标的路径规划策略已有越来越多的研究发表。由于增材制造中路径规划的快速发展以及各种新提出的策略，缺乏关于该主题的全面综述。因此，本文对增材制造路径规划的现状和挑战进行了全面的阐述。本文对路径规划策略进行了综述和讨论，分为三类：提高打印质量、节省材料/时间和实现目标打印性能。本综述的主要发现包括：可以通过将文献中的一些性能更好的策略相结合来开发新的路径规划策略；可以开发一个路径规划平台，以帮助选择具有所需性能的最合适的路径规划策略；未来可以开展考虑能耗的路径规划研究；可以设计一个用于测试路径规划策略性能的基准模型；不同制造性能之间的权衡可以作为未来路径规划设计过程中的一个因素；最后，机器学习可以成为未来进一步改进路径规划策略的有力工具。
