Abstract
Structured light scanning is used to create a digital twin of a manufactured part, where features are extracted to determine if the part meets the designer's intent and required tolerances. This paper describes repeatability and reproducibility analyses for a commercially-available structured light scanning system and measurement artifact. The repeatability study used five repeated scans at 15 measurement positions. Repeatability was assessed by randomly selecting one of the five scans at each of the 15 positions and creating a part mesh. This process was performed 50 times and the statistics for the dimension variations were calculated to isolate the scanning effects only. The same sequence was then performed for 10 of the 15 positions and five of the 15 positions to evaluate the repeatability sensitivity to the number of measurement positions. Reproducibility was assessed by selecting 15 positions to create a mesh and repeating the 15-position measurement sequence 10 times using different positions for each mesh construction. The statistics for the dimension variations were then calculated. This incorporated the effects of both scanning and the position and orientation of the part relative to the scanner. This sequence was repeated for 10-position and five-position scans to evaluate the corresponding sensitivity. Finally, the artifact dimensions from structured light scanning were compared to coordinate measuring machine measurements of the same features.
| Original language | English |
|---|---|
| Pages (from-to) | 873-882 |
| Number of pages | 10 |
| Journal | Manufacturing Letters |
| Volume | 35 |
| DOIs | |
| State | Published - Aug 2023 |
Funding
This work was partially supported by the DOE Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (AMO), under contract DE-AC05-00OR22725. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). The authors would also like to acknowledge support from the NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving from Evolution to Revolution (ERC‐HAMMER) under Award Number EEC-2133630. This work was partially supported by the DOE Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (AMO), under contract DE-AC05-00OR22725. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ). The authors would also like to acknowledge support from the NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving from Evolution to Revolution (ERC‐HAMMER) under Award Number EEC-2133630.
| Funders | Funder number |
|---|---|
| DOE Public Access Plan | |
| NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving | EEC-2133630 |
| Advanced Manufacturing Office | DE-AC05-00OR22725 |
| Advanced Manufacturing Office | |
| Office of Energy Efficiency and Renewable Energy |
Keywords
- Metrology
- Repeatability
- Reproducibility
- Structured light scanning
- Uncertainty