Solving the Big Data (BD) Problem in Advanced Manufacturing (Subcategory for work done at Georgia Tech. Study Process and Design Factors for Additive Manufacturing Improvement)

Technical Report · Tue Sep 01 04:00:00 EDT 2015

DOI:https://doi.org/10.2172/1221177· OSTI ID:1221177

Clark, Brett W. ^[1]; Diaz, Kimberly A. ^[2]; Ochiobi, Chinaza Darlene ^[2]; Paynabar, Kamran ^[2]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Georgia Inst. of Technology, Atlanta, GA (United States)

3D printing originally known as additive manufacturing is a process of making 3 dimensional solid objects from a CAD file. This ground breaking technology is widely used for industrial and biomedical purposes such as building objects, tools, body parts and cosmetics. An important benefit of 3D printing is the cost reduction and manufacturing flexibility; complex parts are built at the fraction of the price. However, layer by layer printing of complex shapes adds error due to the surface roughness. Any such error results in poor quality products with inaccurate dimensions. The main purpose of this research is to measure the amount of printing errors for parts with different geometric shapes and to analyze them for finding optimal printing settings to minimize the error. We use a Design of Experiments framework, and focus on studying parts with cone and ellipsoid shapes. We found that the orientation and the shape of geometric shapes have significant effect on the printing error. From our analysis, we also determined the optimal orientation that gives the least printing error.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1221177
• Report Number(s): SAND2015--7894R; 603818
• Country of Publication: United States
• Language: English