| About this Abstract |
| Meeting |
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Symposium
|
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Presentation Title |
A Novel Metric for Geometric Accuracy Quantification using Point Clouds in Additive Manufacutring |
| Author(s) |
Chuan He, Sushmit Chowdhury, Robert Bedard, Chinedum Okwudire |
| On-Site Speaker (Planned) |
Chuan He |
| Abstract Scope |
Additive manufacturing (AM) possesses a significant advantage over traditional manufacturing methods due to the complexity of parts it can produce. Nevertheless, this complexity introduces challenges in quantifying geometric errors, which significantly affect AM process quality. An automated print quality inspection framework is indispensable for differentiating the performance of various AM processes and machines, particularly in high-value applications. This study presents an approach employing the Iterative Closest Point (ICP) algorithm for registration, establishing a one-to-one correspondence between point clouds based on geometric features. A novel metric, the Similarity Score, is proposed to represent the quality of printed parts. Validated on printed parts, the Similarity Score accurately characterizes print quality with high computational efficiency. Despite the limitations of current commercial software packages and research, this approach holds potential for advancing AM error reduction and compensation strategies. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |