Related Experiment Video
Updated: Oct 20, 2025

Atomically Traceable Nanostructure Fabrication
Published on: July 17, 2015
Uncertainty quantification in dimensions dataset of additive manufactured NIST standard test artifact
Gary Mac1, Hammond Pearce1,2, Ramesh Karri2
1Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, 6 Metrotech Center, Brooklyn, NY 11201, United States.
Abstract:
The printed features on an additive manufactured part will often deviate from the nominal values of the 3D model's features due to the factors such as printer resolution, printing parameters, printing technology, and the measurement method. The National Institute of Standards and Technology (NIST) standard test artifact contains a collection of various features that can be used to characterize a 3D printer's performance and has been used to benchmark metal printers. There is limited documentation on how well different additive manufacturing processes can fabricate the NIST artifact. This dataset records the dimensional uncertainty of selective printed features of the NIST artifact manufactured with polymer and resin printing processes. It contains the post-processing dimensional measurements of geometric features on the printed test artifacts. In order to generate the data, a total of 16 samples of the test artifact were printed with fused deposition modelling (FDM) and stereolithography (SLA) additive manufacturing methods. The percentage error between the measurement of features in the printed samples and their nominal computer aided design (CAD) values are calculated. For future reusability of this data, the same NIST test artifact CAD model can be printed, and the features' measurements can be compared with the dataset presented in this article.
More Related Videos
Related Concept Videos
Uncertainty: Overview
Uncertainty in Measurement: Reading Instruments
Uncertainty in Measurement: Accuracy and Precision
Uncertainty in Measurement: Significant Figures
Estimation of the Physical Quantities
Problem Solving: Dimensional Analysis

