The General Services Administration (GSA) established the National 3D-4D-BIM (Three dimensional- Four Dimensional Building Information Model) Program in 2003. A part of the program involves 3D imaging, and the National Institute of Standards Technology (NIST) was contracted by GSA to assist them in this area. The past GSA-NIST collaboration consisted of: Phase I - BIM Guide for 3D Imaging (Cheok and Lytle, 2009). This document was prepared to provide a general introduction to 3D imaging and its implementation on GSA projects for GSA project managers. Phase II Updating of the BIM Guide for 3D Imaging based on industry feedback. Additionally, a method for objectively assessing the deliverables from 3D imaging data (in this case 2D plans) was developed and documented in Guidelines for Accepting 2D Building Plans (Cheok, et al., 2008). This method provides a systematic answer to the question: Are the dimensional deviations from the derived 2D plans within the specifications stated in the contract? The current effort, Phase III, is the subject of this report. In Phase III, the focus is on evaluating and demonstrating the method proposed in Phase II using an actual GSA facility. In particular, the objective of Phase III is to determine practical/feasible limits for the tolerances (T), sample size (n), and the maximum percent of the population (P) out-of-spec that is acceptable for GSA. In brief, a total of 285 measurements were obtained from a GSA 3D imaging project site by NIST and CMU (Carnegie Mellon University). These measurements were then compared to corresponding measurements extracted from 2D plans or 3D models. Several thousands of simulations were run for different combinations of samples (i.e., to randomize the data sampling) for a given set of n, P, and T. The data collection, data analysis, and findings from Phase III are presented in this report.
Citation: NIST Interagency/Internal Report (NISTIR) - 7659Report Number:
NIST Pub Series: NIST Interagency/Internal Report (NISTIR)
Pub Type: NIST Pubs
3D imaging, acceptance sampling, building, modeling