An efficient curvature-based partitioning of large-scale STL models

Purpose - Rapid prototyping (RP) of large-scale solid models requires the stereolithographic (STL) file to be precisely partitioned. Especially, the selection of cutting positions is critical for the fabrication and assembly of sub-models. The purpose of this paper is to present an efficient curvature-based partitioning for selecting the best-fit loop and decomposing the large complex model into smaller and simpler sub-models with similar-shaped joints, which facilitate the final assembly. Design/methodology/approach - The partition algorithm is benefited from curvature analysis of the model surface, including extracting the feature edges and constructing the feature loops. The efficiency enhancement is achieved by selecting the best-fit loop and constructing the similar-shape joints. The utility of the algorithm is demonstrated by the fabrication of large-scale rapid prototypes. Findings - By using the proposed curvature-based partition algorithm, the reasonability and efficiency of STL model partition can be greatly improved, and the complexity of sub-models has been reduced. It is found that the large-scale model is efficiently partitioned and the sub-models are precisely assembled using the proposed partitioning. Originality/value - The curvature-based partition algorithm is used in the RP field for the first time. Based on the curvature-based partitioning, the reasonability and efficiency of large-scale RP is addressed in this paper.