Journal
JOURNAL OF QUALITY TECHNOLOGY
Volume 50, Issue 4, Pages 379-390Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/00224065.2018.1508274
Keywords
image registration; local smoothing; nonparametric regression; process monitoring; statistical process control; surface estimation
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Funding
- NSF
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Three-dimensional (3D) printing techniques have become popular in recent years. Monitoring the quality of its products is thus important. In the literature, there is little existing research on this topic now, partly because it is a challenging problem with complex data structures. In this article, we propose a nonparametric control chart for Phase II monitoring of the top surfaces of 3D printing products. The top surfaces are focused in this article because they are our major concern regarding the quality of 3D printing products in some applications. Such surfaces are often free-form surfaces. Our proposed method is based on local kernel estimation of free-form surfaces. Before Phase II monitoring, observed data from different products are first geometrically aligned to account for possible movement between the products and a laser scanner during the data acquisition stage. Numerical studies show that the proposed method works well in practice.
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