Abstract

The industrial development of new production processes like additive manufacturing (AM) is making available novel types of complex shapes that go beyond traditionally manufactured geometries and 2.5D free-form surfaces. New challenges must be faced to characterize, model and monitor the natural variability of such complex shapes, since previously proposed methods based on parametric models are not applicable. The present study proposes a methodology that applies to complex shapes represented in the form of triangulated meshes, which is the current standard for AM data format. The method combines a novel bi-directional way to model the deviation between the reconstructed geometry (e.g., via X-ray computed tomography) and the nominal geometry (i.e., the originating 3D model) with a profile monitoring approach for the detection of out-of-control shapes. A paradigmatic example consisting of an egg-shaped trabecular shell representative of real parts produced via AM is used to illustrate the methodology and to test its effectiveness in detecting real geometrical distortions.

摘要

诸如增材制造 (AM) 等新生产工艺的工业发展正在提供新型复杂形状，这些形状超越了传统制造的几何形状和 2.5D 自由曲面。由于先前提出的基于参数模型的方法不适用，因此必须面对新的挑战来表征、建模和监测这种复杂形状的自然变化。本研究提出了一种适用于以三角网格形式表示的复杂形状的方法，这是 AM 数据格式的当前标准。该方法结合了一种新颖的双向方法来模拟重建几何（例如，通过 X 射线计算机断层扫描）和标称几何（即，原始 3D 模型）具有用于检测失控形状的轮廓监控方法。一个由代表通过 AM 生产的真实零件的蛋形小梁壳组成的典型示例用于说明该方法并测试其在检测真实几何变形方面的有效性。