Bianca Maria Colosimo , Federica Garghetti , Marco Grasso , Luca Pagani
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引用次数: 0
Abstract
As advanced production capabilities are moving towards novel types of geometries as well as higher customization demands, a new and more efficient approach for process and part qualification is becoming an urgent need in industry. The layerwise nature of additive manufacturing (AM) potentially allows anticipating qualification tasks in-line and in-process, aiming at reducing the time and costs devoted to post-process inspections, enabling at the same time an early detection of defects since their onset stage. Such opportunity is particularly attractive in the presence of highly complex shapes like lattice structures or metamaterials, which have been increasingly investigated for industrial adoption in various sectors, aiming to achieve enhanced mechanical properties and innovative functionalities. This paper presents a novel methodology to inspect the geometry of lattice structures while the part is being built. The method is specifically designed to tackle the natural variability affecting layerwise images gathered in laser powder bed fusion. To this aim, it combines the segmentation of in-situ powder bed images of solidified layers with a data modelling approach to synthesize the 3-D shape of each unit cell into a 1-D profile representation. Such low-dimensional representation is suitable to quickly detect undesired distortions that may have a detrimental impact on final quality and performance. By using post-process X-ray computed tomography as ground truth reference, this study shows the effectiveness of the proposed approach for in-line inspection, opening a novel and cost-efficient way to address complex shape qualification for lattice structures in AM.
由于先进的生产能力正朝着新型几何形状和更高定制化要求的方向发展,工业界迫切需要一种新的、更有效的工艺和零件鉴定方法。增材制造(AM)的分层特性使其有可能预测在线和过程中的鉴定任务,从而减少用于过程后检测的时间和成本,同时在缺陷出现阶段就能对其进行早期检测。这种机会对于晶格结构或超材料等高度复杂的形状尤其具有吸引力,这些形状越来越多地被研究用于各个领域的工业应用,旨在实现更强的机械性能和创新功能。本文介绍了一种在零件制造过程中检测晶格结构几何形状的新方法。该方法专门用于解决影响激光粉末床融合过程中收集的层间图像的自然变化问题。为此,它将凝固层的原位粉末床图像分割与数据建模方法相结合,将每个单元格的三维形状合成为一维轮廓表示。这种低维表示法适用于快速检测可能对最终质量和性能产生不利影响的不良变形。通过使用后处理 X 射线计算机断层扫描作为地面实况参考,本研究显示了所建议的在线检测方法的有效性,为解决 AM 中晶格结构复杂的形状鉴定问题开辟了一种新颖且具有成本效益的方法。
期刊介绍:
Additive Manufacturing stands as a peer-reviewed journal dedicated to delivering high-quality research papers and reviews in the field of additive manufacturing, serving both academia and industry leaders. The journal's objective is to recognize the innovative essence of additive manufacturing and its diverse applications, providing a comprehensive overview of current developments and future prospects.
The transformative potential of additive manufacturing technologies in product design and manufacturing is poised to disrupt traditional approaches. In response to this paradigm shift, a distinctive and comprehensive publication outlet was essential. Additive Manufacturing fulfills this need, offering a platform for engineers, materials scientists, and practitioners across academia and various industries to document and share innovations in these evolving technologies.