Shapes In A Box -- Disassembling 3D objects for efficient packing and fabrication

TL;DR

This paper presents a novel algorithm for splitting 3D models into parts that can be efficiently packed into boxes for easier transportation and reassembly, addressing challenges in 3D printing and mass customization.

Contribution

It introduces a hierarchical packing-based segmentation algorithm for arbitrary 3D objects, optimizing for tight packing within minimal bounding boxes.

Findings

Algorithm produces satisfactory packing results for various shapes.

Performance is comparable to specialized methods for specific shapes.

Effective heuristic solutions for NP-complete shape packing problem.

Abstract

Modern 3D printing technologies and the upcoming mass-customization paradigm call for efficient methods to produce and distribute arbitrarily-shaped 3D objects. This paper introduces an original algorithm to split a 3D model in parts that can be efficiently packed within a box, with the objective of reassembling them after delivery. The first step consists in the creation of a hierarchy of possible parts that can be tightly packed within their minimum bounding boxes. In a second step, the hierarchy is exploited to extract the (single) segmentation whose parts can be most tightly packed. The fact that shape packing is an NP-complete problem justifies the use of heuristics and approximated solutions whose efficacy and efficiency must be assessed. Extensive experimentation demonstrates that our algorithm produces satisfactory results for arbitrarily-shaped objects while being comparable to ad-hoc methods when specific shapes are considered.