期刊
TECHNOMETRICS
卷 60, 期 2, 页码 169-180出版社
AMER STATISTICAL ASSOC
DOI: 10.1080/00401706.2017.1321585
关键词
Kernel smoothing; Nonparametric regression; Profile monitoring; Registration; Statistical process control; Surface estimation
资金
- NSF grant
In recent years, 3D printing gets more and more popular in manufacturing industries. Quality control of 3D printing products thus becomes an important research problem. However, this problem is challenging due to the facts that (i) the surface of a product from 3D printing can have arbitrary shape, even when the 3D printing process is in-control, (ii) surface observations of the product obtained from a laser scanner may not have regularly spaced locations, and (iii) the overall geometric positions of 3D printing products might be all different, making proper comparison among different products difficult. In this article, we propose a Phase I control chart for monitoring products from 3D printing that addresses all these challenges. Numerical studies show that it works well in practice.
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