Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
Nowadays, packaging waste is a prevalent issue due to the increase in deliveries from online shopping. In this research paper, a new approach to the issue of cardboard box packaging waste is proposed by selecting an optimal box that will contain both regular and irregular products while minimizing wasted volume. The method can be utilized so that packaging workers can select an appropriate, yet sustainable box. For computing a minimal cuboid of irregular objects, the system setup with two cameras is prepared to capture the overhead and sideview images, estimating the box's width, depth, and height in pixels. The proposed 2-step Otsu’s scheme is utilized to avoid inaccuracies created by shadows. With the dimensions of the irregular product calculated and the dimensions of the regular product given, the Largest Area First Fit (LAFF) algorithm is utilized with the dimension of standard Amazon box to optimally package both irregular and regular products together. By placing items with the biggest surface area first, the algorithm effectively stacks items and efficiently proposes an optimal box for a random set of items. Overall, this proposed method of choosing an optimal box size significantly reduces cardboard waste.
Recommended Citation
Kwon, Jimmy and Kwon, Sungmin
()
"Box packaging waste reduction by largest area first fit algorithm and minimum cuboid estimation of irregular shape products,"
Journal of Applied Packaging Research: Vol. 16:
No.
1, Article 1.
Available at:
https://repository.rit.edu/japr/vol16/iss1/1