Online Program

Additive Manufacturing: A Case Study for Characterizing Variability (304250)

Manuel Lopez Martinez, Sandia National Laboratories 
Leslie Melissa Moore, Sandia National Laboratories 
*Lauren Christine Wilson, Sandia National Laboratories 
Joshua Keng Yee, Sandia National Laboratories 

Keywords: Trend-free experimental design, variance component estimation, QMU (quantifying margins and uncertainties), linear mixed and random effects models, metal additive manufacturing.

SAND2021-7063A -Additive manufacturing (AM) provides production advantages with respect to cost, weight, and design complexities. The relative newness of AM compared to conventional methods and its known variability carries non-trivial risk. Building metal AM components with dimensional requirements is of interest for a high-risk application. A statistical experimental design & analysis evaluates the effect of various factors on component acceptance criteria, which demonstrates methodology to provide quantitative evidence in support of an alternative manufacturing process. Analysis includes common data visualization techniques novel to AM process exploration, quantification of margin & uncertainties (QMU) to ensure product quality relative to dimensional limits, and estimation of variance components (within- and between-batch) to inform production sampling and future AM studies. (Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525).