Machines as Craftsmen: Localized Parameter Setting Optimization for Fused Filament Fabrication 3D Printing
Machines as Craftsmen: Localized Parameter Setting Optimization for Fused Filament Fabrication 3D Printing
复制标题
DOI：
10.1002/admt.201800653
复制
发表时间：
2019-03-01
影响因子：
6.8
通讯作者：
Sauti, Godfrey
中科院分区：
文献类型：
--
作者：
Gardner, John M.;Hunt, Kevin A.;Sauti, Godfrey
必须加强3D打印的质量控制和重复性，以充分释放其用途，使其超越原型和非关键应用。机器学习是提高3D打印性能的潜在解决方案，并在缺陷识别和性能预测等领域进行了探索。然而，在机器学习真正使3D打印能够发挥其潜力之前，必须解决关键问题，包括训练所需的非常大的数据集，以及3D打印固有的局部性质，其中最佳参数设置在整个零件中各不相同。这项工作概述了一种将机器学习整合到3D打印过程中的端到端工具。该工具将几何形状、硬件和材料响应时间以及操作员优先级等因素考虑在内，在每个位置选择理想的参数设置。该工具通过纠正熔丝制造部件中常见的视觉缺陷来证明其有效性。图像识别神经网络对零件中的局部缺陷进行分类以创建训练数据。然后，梯度增强分类器根据位置、几何形状和参数设置来预测未来零件中的局部缺陷。该工具根据上述因素选择最佳参数设置。与仅使用全局参数的打印相比，生成的打印显示更高的质量。
Quality control and repeatability of 3D printing must be enhanced to fully unlock its utility beyond prototyping and noncritical applications. Machine learning is a potential solution to improving 3D printing performance and is explored for areas including flaw identification and property prediction. However, critical problems must be resolved before machine learning can truly enable 3D printing to reach its potential, including the very large data sets required for training and the inherently local nature of 3D printing where the optimum parameter settings vary throughout the part. This work outlines an end-to-end tool for integrating machine learning into the 3D printing process. The tool selects the ideal parameter settings at each location, taking into consideration factors such as geometry, hardware and material response times, and operator priorities. The tool demonstrates its usefulness by correcting for visual flaws common in fused filament fabrication parts. An image recognition neural network classifies local flaws in parts to create training data. A gradient boosting classifier then predicts the local flaws in future parts, based on location, geometry, and parameter settings. The tool selects optimum parameter settings based on the aforementioned factors. The resulting prints show increased quality over prints that use global parameters only.