Irregular Packing Based on Principal Component Analysis Methodology

• Main Authors: Baosu Guo, Zhuo Liang, Qingjin Peng, Yongxin Li, Fenghe Wu
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Layout; principal component analysis; computer graphics; optimization method; shape; forward line
• Online Access: https://ieeexplore.ieee.org/document/8500121/

Irregular packing problems exist widely in industrial applications. To obtain better packing results, packing shapes are rotated freely during the packing process. However, equal angle-intervals are commonly used in the existing packing algorithms without considering the shape contour features, which may miss the best packing positions with the reduced packing quality. To solve this problem, an irregular packing algorithm is proposed based on a principal component analysis methodology in this paper. The principal components of convex features on the shapes are calculated. The rotation angles are then searched according to the first principal components. Finally, the shapes are rotated and packed based on the rotation angles. Experimental results show that the packing time is reduced and the material utilization is improved by the proposed algorithm.